
How I use Git worktrees to work on 4 things at once without losing my mind
I had a production hotfix, two feature branches, and a code review all due by end of day. Stashing was not going to cut it.
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Thoughts on AI engineering, responsible automation, and building systems that matter.

I had a production hotfix, two feature branches, and a code review all due by end of day. Stashing was not going to cut it.
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The bug crashed production every Tuesday at 2 AM. Only Tuesday. Only 2 AM. The logs showed nothing. The monitoring showed nothing. Three days later I found it - and the fix was not code.
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AI can write code quickly. That does not make the code safe, maintainable, or production-ready. Over time I built a testing workflow that treats AI output like a fast junior teammate: useful, productive, and never above verification.
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The strongest automation systems I trust are not the ones that pretend humans disappeared. They are the ones that know exactly when a human should stay in the loop, what decision that human should make, and how the system should continue afterward.
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Laravel gets called magical when it hides work developers expected to see. After years of building PHP systems, I think the real question is not whether Laravel has magic. It is whether your team knows where the magic ends.
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An AI feature can look impressive in a request-response demo and still collapse in production. Queues turn slow, unpredictable model calls into workflows that can be retried, inspected, limited, and trusted.
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I needed to build a CLI tool that could orchestrate Docker containers, manage Git worktrees, allocate ports, and run a 9-stage pipeline in under a minute. I evaluated five options. The winner surprised me.
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The first time a lawyer asked me "but who is liable when the AI makes a wrong decision?" I realized I had been building systems without understanding the world they operate in.
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